Papers Multi-class Classification
“Multi-class Classification” 태그가 달린 논문 1,008편 · 필터 해제
ltzGLUE: Luxembourgish General Language Understanding Evaluation
This paper presents ltzGLUE, the first Natural Language Understanding (NLU) benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for English. Although NLU tasks are available for many European languages …
Natural Language UnderstandingMulti-class ClassificationIntent ClassificationEarly Detection of Alzheimer's Disease Using Explainable Machine Learning on Clinical Biomarkers: A Multi-Class Classification Study Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset
Background: Alzheimer's disease (AD) affects over 55 million people worldwide. Accurate, interpretable detection of normal cognition (NC), mild cognitive impairment (MCI), and AD from routine clinical assessments remains…
Multi-class ClassificationFeature ImportanceA Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security
The rapid adoption of the Internet of Medical Things (IoMT) is transforming healthcare by enabling seamless connectivity among medical devices, systems, and services. However, it also introduces serious cybersecurity and…
Interpretable Machine LearningMulti-class ClassificationBinary ClassificationIntrusion DetectionProbabilistic classification from possibilistic data: computing Kullback-Leibler projection with a possibility distribution
We consider learning with possibilistic supervision for multi-class classification. For each training instance, the supervision is a normalized possibility distribution that expresses graded plausibility over the classes…
Natural Language InferenceMulti-class ClassificationHarassGuard: Detecting Harassment Behaviors in Social Virtual Reality with Vision-Language Models
Social Virtual Reality (VR) platforms provide immersive social experiences but also expose users to serious risks of online harassment. Existing safety measures are largely reactive, while proactive solutions that detect…
Multi-class ClassificationBinary ClassificationPrompt EngineeringDiffusion-Based Feature Denoising with NNMF for Robust handwritten digit multi-class classification
This work presents a robust multi-class classification framework for handwritten digits that combines diffusion-driven feature denoising with a hybrid feature representation. Inspired by our previous work on brain tumor …
Brain Tumor ClassificationMulti-class ClassificationImproving Automated Wound Assessment Using Joint Boundary Segmentation and Multi-Class Classification Models
Accurate wound classification and boundary segmentation are essential for guiding clinical decisions in both chronic and acute wound management. However, most existing AI models are limited, focusing on a narrow set of w…
Multi-class ClassificationMaterial Identification using Multi-Modal Intrinsic Radiation and Radiography
We investigate multi-modal material identification for special nuclear material (SNM) configurations using a combination of X-ray radiography, high-resolution γ-ray spectroscopy, and neutron multiplicity measurements. We…
Multi-class ClassificationBeyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers
Through an analysis of arXiv papers, we report several shifts in word usage that are likely driven by large language models (LLMs) but have not previously received sufficient attention, such as the increased frequency of…
Multi-class ClassificationSemi-Supervised Learning with Balanced Deep Representation Distributions
Semi-Supervised Text Classification (SSTC) mainly works under the spirit of self-training. They initialize the deep classifier by training over labeled texts; and then alternatively predict unlabeled texts as their pseud…
Semi-Supervised Text ClassificationMulti-Label ClassificationMulti-class ClassificationA Generalised Exponentiated Gradient Approach to Enhance Fairness in Binary and Multi-class Classification Tasks
The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced various methods for bias mitigation in binary classification tasks, the is…
Multi-class ClassificationBinary ClassificationVariational Phasor Circuits for Phase-Native Brain-Computer Interface Classification
We present the Variational Phasor Circuit (VPC), a deterministic classical learning architecture on the continuous $S^1$ unit-circle manifold. Inspired by variational quantum circuits, VPC replaces dense weight matrices …
Multi-class ClassificationDeep learning based intelligent IDS for Large-scale IoT networks
The proliferation of large-scale IoT networks has been both a blessing and a curse. Not only has it revolutionized the way organizations operate by increasing the efficiency of automated procedures, but it has also simpl…
Multi-class ClassificationIntrusion DetectionSimplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classification
We propose a conjugate and calibrated Gaussian process (GP) model for multi-class classification by exploiting the geometry of the probability simplex. Our approach uses Aitchison geometry to map simplex-valued class pro…
Multi-class ClassificationA Hybrid AI and Rule-Based Decision Support System for Disease Diagnosis and Management Using Labs
This research paper outlines the development and implementation of a novel Clinical Decision Support System (CDSS) that integrates AI predictive modeling with medical knowledge bases. It utilizes the quantifiable informa…
Multi-class ClassificationMultimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis
Magnetic Resonance Imaging (MRI) provides detailed structural information, while functional MRI (fMRI) captures temporal brain activity. In this work, we present a multimodal deep learning framework that integrates MRI a…
Multi-class ClassificationMultimodal Deep LearningData AugmentationDetection of Illicit Content on Online Marketplaces using Large Language Models
Online marketplaces, while revolutionizing global commerce, have inadvertently facilitated the proliferation of illicit activities, including drug trafficking, counterfeit sales, and cybercrimes. Traditional content mode…
parameter-efficient fine-tuningMulti-class ClassificationBinary ClassificationPCOV-KWS: Multi-task Learning for Personalized Customizable Open Vocabulary Keyword Spotting
As advancements in technologies like Internet of Things (IoT), Automatic Speech Recognition (ASR), Speaker Verification (SV), and Text-to-Speech (TTS) lead to increased usage of intelligent voice assistants, the demand f…
Multi-class ClassificationSpeaker VerificationMulti-Task LearningSpeech RecognitionPretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification
We investigate a quantum-inspired approach to supervised multi-class classification based on the Pretty Good Measurement (PGM), viewed as an operator-valued decision rule derived from quantum state discrimination. The me…
Multi-class ClassificationImplicit Bias and Convergence of Matrix Stochastic Mirror Descent
We investigate Stochastic Mirror Descent (SMD) with matrix parameters and vector-valued predictions, a framework relevant to multi-class classification and matrix completion problems. Focusing on the overparameterized re…
Multi-class Classification